Analytics and Data Science Major: Data Science Option B.S.

Major in Analytics and Data Science Data Science Option
Analytics and Data Science Major: Data Science Option B.S.

Program Overview

What is the data science option in analytics and data science?

This option in the analytics and data science degree program will give you the skills to pursue original research or an advanced degree in data science. You’ll gain a deep understanding of concepts from mathematics and computer science such as probability theory, statistical analysis, predictive modeling, algorithms, machine learning, and data science.

Why study analytics and data science at UNH?

UNH was one of the first universities in the country to offer an undergraduate-level degree in analytics and data science. Our programs take a multidisciplinary approach that incorporates experiential education, professional development, projects and work experience. We partner with local businesses to give you the real-world experience that sets you apart, and our analytics majors have access to internships at many high-profile organizations. You’ll learn the cutting-edge technical skills you need to manage, distill, and interpret data for industries from finance to healthcare to marketing and advertising. The data science option is available only through the Durham campus.

Potential careers

  • Actuary
  • Business analyst
  • Consultant
  • Data engineer
  • Data scientist
  • Management analyst
  • Market research analyst
  • Statistician
  • Quantitative analyst
Department of Computer Science
Kingsbury Hall N229, 33 Academic Way
Durham, NH 03824

Phone: (603) 862.3778

Curriculum & Requirements

The option in Data Science is intended for students interested in pursuing advanced degrees and conducting original research in data science. The option in data science places its emphasis on the theoretical mathematical and computational underpinnings of modern data science.

Program Objectives

This program has been designed to prepare students for professional careers working with data, with an emphasis on the extraction of meaning from data. The program is not targeted to any one industry; rather, it provides a flexible, practical skillset that can be applied widely. This skillset includes elements of computer science, applied mathematics and statistics, communication skills, and business savvy. Graduates of the bachelor of science in analytics and data science program are expected to have:

  • An understanding of the role of data in guiding decision-making in industry
  • An understanding of how data is generated, stored, and accessed
  • An understanding of data security
  • An understanding of the ethical use of data
  • An understanding of structured vs. unstructured data
  • An understanding of the methods, statistical and other, used to derive actionable information from data
  • Experience with multiple programming languages
  • Experience with multiple statistical and data analysis software programs
  • The ability to communicate detailed, technical information to a variety of audiences clearly and concisely, without the use of jargon
  • The ability to work effectively, both as an individual or as a member of a team
  • The ability to successfully lead a team
  • The ability to adapt to a dynamic, rapidly changing work environment
  • Completed projects and other work experiences on a larger scale than is typical in a bachelor's degree program.

During the course of the program, students will demonstrate their acquisition of these skills by successfully completing their program coursework, their internship experience, and their capstone project.

Successful completion of the program entails earning at least 128 credits, meeting the requirements of the University's Discovery program, completing all of the 22 required courses in the major as listed below, including the capstone course, the internship preparedness course, and a three-credit internship. In all major courses, the minimum allowable grade is a C-. The minimum overall GPA for graduation is 2.0. Transfer students may transfer up to a maximum of 32 credits to satisfy major requirements (not counting those courses used to satisfy Discovery requirements).

Program Requirements

MATH 425Calculus I4
MATH 426Calculus II4
MATH 528Multidimensional Calculus4
MATH 531Mathematical Proof4
MATH 539Introduction to Statistical Analysis4
or MATH 644 Statistics for Engineers and Scientists
MATH 645Linear Algebra for Applications4
MATH 738Data Mining and Predictive Analytics4
MATH 755Probability with Applications4
MATH 756Principles of Statistical Inference4
MATH 797Senior Seminar 14
or MATH 798 Senior Project
Computer Science
CS 414From Problems to Algorithms to Programs4
or CS 415 Introduction to Computer Science I
CS 417From Programs to Computer Science4
or CS 416 Introduction to Computer Science II
CS 659Introduction to the Theory of Computation4
CS 750Machine Learning4
CS 758Algorithms4
CS 775Database Systems4
ENGL 502Professional and Technical Writing4
Analytics Course
DATA 557Introduction to Data Science and Analytics4
Select three electives 212
Total Credits84

For additional information about the Analytics and Data Science: Data Science Option, contact Jeremiah Johnson, program coordinator, at (603) 641-4127 or

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